The employees perspective on the challenges faced when starting a new job remotely

Due to the mandatory lockdown, resulted from the COVID-19 pandemic, employees had to start working remotely and companies had to change their onboarding experience to online. So, this research goal is to discover if employees that started working remotely faced new challenges. For that, a qualitative approach was conducted, and it was concluded that these employees miss more the office than the remaining, since they did not had a previous personal experience with the colleagues

An electro-rheological study of the nematic liquid crystal 4-n-heptyl-4'-cyanobiphenyl

An experimental and theoretical study of the electro-rheological effects observed in the nematic phase of 4-n-heptyl-4'-cyanobiphenyl has been conducted. This liquid crystal appears to be a model system, in which the observed rheological behaviour can be interpreted by the Leslie-Ericksen continuum theory for low molecular weight liquid crystals. Flow curves are illustrated at different temperatures and under the influence of an external electric field ranging from 0 to 3 kV mm-1, applied perpendicular to the direction of flow. Also presented is the apparent viscosity as a function of temperature, over similar values of electric field, obtained at different shear rates. A master flow curve has been constructed for each temperature by dividing the shear rate by the square of the electric field and multiplying by the square of a reference value of electric field. In a log-log plot, two Newtonian plateaux are found to appear at low and high shear rates, connected by a shear-thinning region. We have applied the Leslie-Ericksen continuum theory, in which the director alignment angle is a function of the electric field and the flow field boundary conditions are neglected, to determine viscoelastic parameters and the dielectric anisotropy

Rheo-optical characterization of liquid crystalline acetoxypropylcellulose melt undergoing large shear flow and relaxation after flow cessation

The rheological and structural characteristics of acetoxypropylcellulose (APC) nematic melt are studied at shear rates ranging from 10 s 1 to 1000 s 1 which are relevant to extrusion based processes. APC shows a monotonic shear thinning behavior over the range of shear rates tested. The negative extrudate-swell shows a minimum when a critical shear rate g_ c is reached. For shear rates smaller than g_ c, the flowinduced texture consists of two set of bands aligned parallel and normal to the flow direction. At shear rates larger than g_ c, the flow induced texture is reminiscent of a 2 fluids structure. Close to the shearing walls, domains elongated along the flow direction and stacked along the vorticity are imaged with POM, whereas SALS patterns indicate that the bulk of the sheared APC is made of elliptical domains oriented along the vorticity. No full nematic alignment is achieved at the largest shear rate tested. Below g_ c, the stress relaxation is described by a stretched exponential. Above g_ c, the stress relaxation is described by a fast and a slow process. The latter coincides with the growth of normal bands thicknesses, as the APC texture after flow cessation consists of two types of bands with parallel and normal orientations relative to the flow direction. Both bands thicknesses do not depend on the applied shear rate, in contrast to their orientation.This work was partially supported by the Portuguese Science and Technology Foundation through projects, PTDC/CTM/099595/2008, PTDC/CTM/101776/2008, PTDC/CTM-POL/1484/2012 and UID/CTM/500025/2013. S.N. Fernandes and J.P. Canejo acknowledge FCT for grants SFRH/BPD/78430/2011 and SFRH/BPD/101041/2014, respectively. Funding for project "Matepro e Optimizing Materials and Processes", with reference NORTE-07-0124-FEDER-000037 FEDER COMPETE, is also acknowledged

An Item-Level Analysis of the Posttraumatic Stress Disorder Checklist and the Posttraumatic Growth Inventory and Its Associations With Challenge to Core Beliefs and Rumination

Background: Previous studies have found that rumination and challenge to core beliefs may have a predictive effect on Posttraumatic Stress Disorder (PTSD) and Posttraumatic Growth (PTG) among different samples. In addition, there is some evidence that these variables have different effects on PTSD and PTG, although the latter construct has been the target of a larger body of research and theoretical models. The main objective of the current study is to examine the effect of challenge to core beliefs, intrusive rumination, and deliberate rumination on PTSD and PTG, through an item-level analyses.Methods: The sample was composed of 205 Portuguese women who had been given a breast cancer diagnosis (M = 54.32, SD = 10.05), and who completed the following self-administered questionnaires: the Posttraumatic Stress Disorder Checklist (PCL-C); the Posttraumatic Growth Inventory (PTGI); the Core Beliefs Inventory; and the Event Related Rumination Inventory. Two multivariate multiple regression analyses, using each item of the PCL-C and the PTGI as dependent variables, were conducted.Results: The results demonstrated that challenges to core beliefs predict 17 of the 21 PTGI items and 12 of the 17 PCL-C items. All but one item of the PCL-C are predicted by intrusive rumination, while the variance of only 4 items of the PTGI are explained by deliberate rumination.Conclusion: These findings indicate that women with breast cancer who tend to display higher levels of intrusive rumination are more likely to report PTSD symptoms, and that an examination of one’s core beliefs is predictor of both positive and negative outcomes. In spite of the proven effect of challenge to core beliefs on both variables, this study suggests that this effect has only a minor influence on PTSD, in addition to confirming its major impact on PTG

Jovens Solistas da Metropolitana

Brochura de sala do concerto realizado pelos Jovens Solistas da Metropolitana a 29 de Maio de 2021 no MUSEU NACIONAL da MÚSICA em Lisboa no âmbito da Temporada 2020/2021 da Metropolitana. O programa do concerto foi preenchido com obras de Debussy, Stravinsky, Cuninghame, Mozart e Bottesini. Desenvolvendo uma ponte pedagógica inédita entre a prática e o ensino musical, a ANSO é a única escola do país que forma maestros, instrumentistas de orquestra e pianistas vocacionados para música de câmara. Ao longo dos seus quase 30 anos, mudou o panorama cultural em Portugal, sendo muitos os seus alunos a entrar nas mais exigentes instituições de ensino e formações internacionais. Mais premiada escola nacional desta área, as novas gerações de intérpretes e diretores musicais que lança são reconhecidas pela qualidade. A música de câmara é uma das vertentes fundamentais da Academia Nacional Superior de Orquestra, que todos os anos apresenta o ciclo Jovens Solistas da Metropolitana.N/

Dynamics and determinants of SARS-CoV-2 RT-PCR testing on symptomatic individuals attending healthcare centers during 2020 in Bahia, Brazil

RT-PCR testing data provides opportunities to explore regional and individual determinants of test positivity and surveillance infrastructure. Using Generalized Additive Models, we explored 222,515 tests of a random sample of individuals with COVID-19 compatible symptoms in the Brazilian state of Bahia during 2020. We found that age and male gender were the most significant determinants of test positivity. There was evidence of an unequal impact among socio-demographic strata, with higher positivity among those living in areas with low education levels during the first epidemic wave, followed by those living in areas with higher education levels in the second wave. Our estimated probability of testing positive after symptom onset corroborates previous reports that the probability decreases with time, more than halving by about two weeks and converging to zero by three weeks. Test positivity rates generally followed state-level reported cases, and while a single laboratory performed ~90% of tests covering ~99% of the state's area, test turn-around time generally remained below four days. This testing effort is a testimony to the Bahian surveillance capacity during public health emergencies, as previously witnessed during the recent Zika and Yellow Fever outbreaks

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost